Publication detail

CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability

KUNKA, A. LACKO, D. ŠTOURAČ, J. DAMBORSKÝ, J. PROKOP, Z. MAZURENKO, S.

Original Title

CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability

Type

journal article in Web of Science

Language

English

Original Abstract

The importance of the quantitative description of protein unfolding and aggregation for the rational design of stability or understanding the molecular basis of protein misfolding diseases is well established. Protein thermostability is typically assessed by calorimetric or spectroscopic techniques that monitor different complementary signals during unfolding. The CalFitter webserver has already proved integral to deriving invaluable energy parameters by global data analysis. Here, we introduce CalFitter 2.0, which newly incorporates singular value decomposition (SVD) of multi-wavelength spectral datasets into the global fitting pipeline. Processed time- or temperature-evolved SVD components can now be fitted together with other experimental data types. Moreover, deconvoluted basis spectra provide spectral fingerprints of relevant macrostates populated during unfolding, which greatly enriches the information gains of the CalFitter output. The SVD analysis is fully automated in a  highly interactive module, providing access to the results to users without any prior knowledge of the underlying mathematics. Additionally, a novel data uploading wizard has been implemented to facilitate rapid and easy uploading of multiple datasets. Together, the newly introduced changes significantly improve the user experience, making this software a unique, robust, and interactive platform for the analysis of protein thermal denaturation data.

Keywords

fluorescence, calorimetry, resolution, state

Authors

KUNKA, A.; LACKO, D.; ŠTOURAČ, J.; DAMBORSKÝ, J.; PROKOP, Z.; MAZURENKO, S.

Released

5. 7. 2022

ISBN

1362-4962

Periodical

Nucleic Acids Research

Year of study

50

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

145

Pages to

151

Pages count

7

URL

https://watermark.silverchair.com/gkac378.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAt8wggLbBgkqhkiG9w0BBwagggLMMIICyAIBADCCAsEGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQM6mnogQLGRDLO_t5jAgEQgIICkgBAjLYrvaDf6iP6XH99tWgNvN-saAJIyGEw-eFFniYTYL2

BibTex

@article{BUT182263,
  author="Antonín {Kunka} and Dávid {Lacko} and Jan {Štourač} and Jiří {Damborský} and Zbyněk {Prokop} and Stanislav {Mazurenko}",
  title="CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability",
  journal="Nucleic Acids Research",
  year="2022",
  volume="50",
  number="1",
  pages="145--151",
  doi="10.1093/nar/gkac378",
  issn="1362-4962",
  url="https://watermark.silverchair.com/gkac378.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAt8wggLbBgkqhkiG9w0BBwagggLMMIICyAIBADCCAsEGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQM6mnogQLGRDLO_t5jAgEQgIICkgBAjLYrvaDf6iP6XH99tWgNvN-saAJIyGEw-eFFniYTYL2"
}